Gathered loads/extractelements/extractvalue instructions should be
checked if they can represent a vector reordering node too and their
order should ve taken into account for better graph reordering analysis/
Also, if the gather node has reused scalars, they must be reordered
instead of the scalars themselves.
Differential Revision: https://reviews.llvm.org/D112454
Gathered loads/extractelements/extractvalue instructions should be
checked if they can represent a vector reordering node too and their
order should ve taken into account for better graph reordering analysis/
Also, if the gather node has reused scalars, they must be reordered
instead of the scalars themselves.
Differential Revision: https://reviews.llvm.org/D112454
Gathered loads/extractelements/extractvalue instructions should be
checked if they can represent a vector reordering node too and their
order should ve taken into account for better graph reordering analysis/
Also, if the gather node has reused scalars, they must be reordered
instead of the scalars themselves.
Differential Revision: https://reviews.llvm.org/D112454
Need to emit select(cmp) instructions for poison-safe forms of select
ops. Currently alive reports that `Target is more poisonous than source`
for operations we generating for such instructions.
https://alive2.llvm.org/ce/z/FiNiAA
Differential Revision: https://reviews.llvm.org/D112562
The final reduction nodes should not be reordered, the order does not
matter for reductions. Also, it might be profitable to vectorize smaller
reduction trees, reduction cost may compensate small tree cost.
Part of D111574
Differential Revision: https://reviews.llvm.org/D112467
Need to change the order of the reduction/binops args pair vectorization
attempts. Need to try to find the reduction at first and postpone
vectorization of binops args. This may help to find more reduction
patterns and vectorize them.
Part of D111574.
Differential Revision: https://reviews.llvm.org/D112224
Vectorization of PHIs and stores very similar, it might be beneficial to
try to revectorize stores (like PHIs) if the total number of stores with
the same/alternate opcode is less than the vector size but number of
stores with the same type is larger than the vector size.
Differential Revision: https://reviews.llvm.org/D109831
Need to follow the order of the reused scalars from the
ReuseShuffleIndices mask rather than rely on the natural order.
Differential Revision: https://reviews.llvm.org/D111898
Need to check that either Idx is UndefMaskElem and value is UndefValue
or Idx is valid and value is the same as the scalar value in the node.
Differential Revision: https://reviews.llvm.org/D111802
We need to be better at exposing the comparison predicate to getCmpSelInstrCost calls as some targets (e.g. X86 SSE) have very different costs for different comparisons (PR48337), and we can't always rely on the optional Instruction argument.
This initial commit requires explicit condition type and predicate arguments. The next step will be to review a lot of the existing getCmpSelInstrCost calls which have used BAD_ICMP_PREDICATE even when the predicate is known.
Differential Revision: https://reviews.llvm.org/D111024
Some initially gathered nodes missed the check for the reused scalars,
which leads to high gather cost. Such nodes still can be represented as
m gathers + shuffle instead of n gathers, where m < n.
Differential Revision: https://reviews.llvm.org/D111153
D104809 changed `buildTree_rec` to check for extract element instructions
with scalable types. However, if the extract is extended or truncated,
these changes do not apply and we assert later on in isShuffle(), which
attempts to cast the type of the extract to FixedVectorType.
Reviewed By: ABataev
Differential Revision: https://reviews.llvm.org/D110640
Try to improve vectorization of the PHI nodes by trying to vectorize
similar instructions at the size of the widest possible vectors, then
aggregating with compatible type PHIs and trying to vectoriza again and
only if this failed, try smaller sizes of the vector factors for
compatible PHI nodes. This restores performance of several benchmarks
after tuning of the fp/int conversion instructions costs.
Differential Revision: https://reviews.llvm.org/D108740
The instruction extractelement/extractvalue are not required to
be scheduled since they only depend on the source vector/aggregate (with
constant indices), smae applies to the parent basic block checks.
Improves compile time and saves scheduling budget.
Differential Revision: https://reviews.llvm.org/D108703
We see that it might otherwise do:
%10 = getelementptr {}**, <2 x {}***> %9, <2 x i32> <i32 10, i32 4>
%11 = bitcast <2 x {}***> %10 to <2 x i64*>
...
%27 = extractelement <2 x i64*> %11, i32 0
%28 = bitcast i64* %27 to <2 x i64>*
store <2 x i64> %22, <2 x i64>* %28, align 4, !tbaa !2
Which is an out-of-bounds store (the extractelement got offset 10
instead of offset 4 as intended). With the fix, we correctly generate
extractelement for i32 1 and generate correct code.
Differential Revision: https://reviews.llvm.org/D106613
Avoid relying on the default cost kinds in TTI calls (we already do this in other places in SLP) - noticed while trying to see how much work it'd be to extend D110242 and remove all remaining uses of default CostKind arguments.
Reworked reordering algorithm. Originally, the compiler just tried to
detect the most common order in the reordarable nodes (loads, stores,
extractelements,extractvalues) and then fully rebuilding the graph in
the best order. This was not effecient, since it required an extra
memory and time for building/rebuilding tree, double the use of the
scheduling budget, which could lead to missing vectorization due to
exausted scheduling resources.
Patch provide 2-way approach for graph reodering problem. At first, all
reordering is done in-place, it doe not required tree
deleting/rebuilding, it just rotates the scalars/orders/reuses masks in
the graph node.
The first step (top-to bottom) rotates the whole graph, similarly to the previous
implementation. Compiler counts the number of the most used orders of
the graph nodes with the same vectorization factor and then rotates the
subgraph with the given vectorization factor to the most used order, if
it is not empty. Then repeats the same procedure for the subgraphs with
the smaller vectorization factor. We can do this because we still need
to reshuffle smaller subgraph when buildiong operands for the graph
nodes with lasrger vectorization factor, we can rotate just subgraph,
not the whole graph.
The second step (bottom-to-top) scans through the leaves and tries to
detect the users of the leaves which can be reordered. If the leaves can
be reorder in the best fashion, they are reordered and their user too.
It allows to remove double shuffles to the same ordering of the operands in
many cases and just reorder the user operations instead. Plus, it moves
the final shuffles closer to the top of the graph and in many cases
allows to remove extra shuffle because the same procedure is repeated
again and we can again merge some reordering masks and reorder user nodes
instead of the operands.
Also, patch improves cost model for gathering of loads, which improves
x264 benchmark in some cases.
Gives about +2% on AVX512 + LTO (more expected for AVX/AVX2) for {625,525}x264,
+3% for 508.namd, improves most of other benchmarks.
The compile and link time are almost the same, though in some cases it
should be better (we're not doing an extra instruction scheduling
anymore) + we may vectorize more code for the large basic blocks again
because of saving scheduling budget.
Differential Revision: https://reviews.llvm.org/D105020
This renames the primary methods for creating a zero value to `getZero`
instead of `getNullValue` and renames predicates like `isAllOnesValue`
to simply `isAllOnes`. This achieves two things:
1) This starts standardizing predicates across the LLVM codebase,
following (in this case) ConstantInt. The word "Value" doesn't
convey anything of merit, and is missing in some of the other things.
2) Calling an integer "null" doesn't make any sense. The original sin
here is mine and I've regretted it for years. This moves us to calling
it "zero" instead, which is correct!
APInt is widely used and I don't think anyone is keen to take massive source
breakage on anything so core, at least not all in one go. As such, this
doesn't actually delete any entrypoints, it "soft deprecates" them with a
comment.
Included in this patch are changes to a bunch of the codebase, but there are
more. We should normalize SelectionDAG and other APIs as well, which would
make the API change more mechanical.
Differential Revision: https://reviews.llvm.org/D109483
SLPVectorizer currently uses AA::isNoAlias() to determine whether
two locations alias. This does not work if one of the instructions
is a call. Instead, we should check getModRefInfo(), which
determines whether an arbitrary instruction modifies or references
a given location.
Among other things, this prevents @llvm.experimental.noalias.scope.decl()
and other inaccessiblmemonly intrinsics from interfering with SLP
vectorization.
Differential Revision: https://reviews.llvm.org/D109012
Reworked reordering algorithm. Originally, the compiler just tried to
detect the most common order in the reordarable nodes (loads, stores,
extractelements,extractvalues) and then fully rebuilding the graph in
the best order. This was not effecient, since it required an extra
memory and time for building/rebuilding tree, double the use of the
scheduling budget, which could lead to missing vectorization due to
exausted scheduling resources.
Patch provide 2-way approach for graph reodering problem. At first, all
reordering is done in-place, it doe not required tree
deleting/rebuilding, it just rotates the scalars/orders/reuses masks in
the graph node.
The first step (top-to bottom) rotates the whole graph, similarly to the previous
implementation. Compiler counts the number of the most used orders of
the graph nodes with the same vectorization factor and then rotates the
subgraph with the given vectorization factor to the most used order, if
it is not empty. Then repeats the same procedure for the subgraphs with
the smaller vectorization factor. We can do this because we still need
to reshuffle smaller subgraph when buildiong operands for the graph
nodes with lasrger vectorization factor, we can rotate just subgraph,
not the whole graph.
The second step (bottom-to-top) scans through the leaves and tries to
detect the users of the leaves which can be reordered. If the leaves can
be reorder in the best fashion, they are reordered and their user too.
It allows to remove double shuffles to the same ordering of the operands in
many cases and just reorder the user operations instead. Plus, it moves
the final shuffles closer to the top of the graph and in many cases
allows to remove extra shuffle because the same procedure is repeated
again and we can again merge some reordering masks and reorder user nodes
instead of the operands.
Also, patch improves cost model for gathering of loads, which improves
x264 benchmark in some cases.
Gives about +2% on AVX512 + LTO (more expected for AVX/AVX2) for {625,525}x264,
+3% for 508.namd, improves most of other benchmarks.
The compile and link time are almost the same, though in some cases it
should be better (we're not doing an extra instruction scheduling
anymore) + we may vectorize more code for the large basic blocks again
because of saving scheduling budget.
Differential Revision: https://reviews.llvm.org/D105020
Reworked reordering algorithm. Originally, the compiler just tried to
detect the most common order in the reordarable nodes (loads, stores,
extractelements,extractvalues) and then fully rebuilding the graph in
the best order. This was not effecient, since it required an extra
memory and time for building/rebuilding tree, double the use of the
scheduling budget, which could lead to missing vectorization due to
exausted scheduling resources.
Patch provide 2-way approach for graph reodering problem. At first, all
reordering is done in-place, it doe not required tree
deleting/rebuilding, it just rotates the scalars/orders/reuses masks in
the graph node.
The first step (top-to bottom) rotates the whole graph, similarly to the previous
implementation. Compiler counts the number of the most used orders of
the graph nodes with the same vectorization factor and then rotates the
subgraph with the given vectorization factor to the most used order, if
it is not empty. Then repeats the same procedure for the subgraphs with
the smaller vectorization factor. We can do this because we still need
to reshuffle smaller subgraph when buildiong operands for the graph
nodes with lasrger vectorization factor, we can rotate just subgraph,
not the whole graph.
The second step (bottom-to-top) scans through the leaves and tries to
detect the users of the leaves which can be reordered. If the leaves can
be reorder in the best fashion, they are reordered and their user too.
It allows to remove double shuffles to the same ordering of the operands in
many cases and just reorder the user operations instead. Plus, it moves
the final shuffles closer to the top of the graph and in many cases
allows to remove extra shuffle because the same procedure is repeated
again and we can again merge some reordering masks and reorder user nodes
instead of the operands.
Also, patch improves cost model for gathering of loads, which improves
x264 benchmark in some cases.
Gives about +2% on AVX512 + LTO (more expected for AVX/AVX2) for {625,525}x264,
+3% for 508.namd, improves most of other benchmarks.
The compile and link time are almost the same, though in some cases it
should be better (we're not doing an extra instruction scheduling
anymore) + we may vectorize more code for the large basic blocks again
because of saving scheduling budget.
Differential Revision: https://reviews.llvm.org/D105020
The instruction extractelement/extractvalue are not required to
be scheduled since they only depend on the source vector/aggregate (with
constant indices), smae applies to the parent basic block checks.
Improves compile time and saves scheduling budget.
Differential Revision: https://reviews.llvm.org/D108703
If the vectorized insertelements instructions form indentity subvector
(the subvector at the beginning of the long vector), it is just enough
to extend the vector itself, no need to generate inserting subvector
shuffle.
Differential Revision: https://reviews.llvm.org/D107494
If the vectorized insertelements instructions form indentity subvector
(the subvector at the beginning of the long vector), it is just enough
to extend the vector itself, no need to generate inserting subvector
shuffle.
Differential Revision: https://reviews.llvm.org/D107344
Replace insertelement instructions for splats with just single
insertelement + broadcast shuffle. Also, try to merge these instructions
if they come from the same/shuffled gather node.
Differential Revision: https://reviews.llvm.org/D107104
For the nodes with reused scalars the user may be not only of the size
of the final shuffle but also of the size of the scalars themselves,
need to check for this. It is safe to just modify the check here, since
the order of the scalars themselves is preserved, only indeces of the
reused scalars are changed. So, the users with the same size as the
number of scalars in the node, will not be affected, they still will get
the operands in the required order.
Reported by @mstorsjo in D105020.
Differential Revision: https://reviews.llvm.org/D107080
If the instruction was previously deleted, it should not be treated as
an external user. This fixes cost estimation and removes dead
extractelement instructions.
Differential Revision: https://reviews.llvm.org/D107106
Need to check that the minimum acceptable vector factor is at least 2,
not 0, to avoid compiler crash during gathered loads analysis.
Differential Revision: https://reviews.llvm.org/D107058
Reworked reordering algorithm. Originally, the compiler just tried to
detect the most common order in the reordarable nodes (loads, stores,
extractelements,extractvalues) and then fully rebuilding the graph in
the best order. This was not effecient, since it required an extra
memory and time for building/rebuilding tree, double the use of the
scheduling budget, which could lead to missing vectorization due to
exausted scheduling resources.
Patch provide 2-way approach for graph reodering problem. At first, all
reordering is done in-place, it doe not required tree
deleting/rebuilding, it just rotates the scalars/orders/reuses masks in
the graph node.
The first step (top-to bottom) rotates the whole graph, similarly to the previous
implementation. Compiler counts the number of the most used orders of
the graph nodes with the same vectorization factor and then rotates the
subgraph with the given vectorization factor to the most used order, if
it is not empty. Then repeats the same procedure for the subgraphs with
the smaller vectorization factor. We can do this because we still need
to reshuffle smaller subgraph when buildiong operands for the graph
nodes with lasrger vectorization factor, we can rotate just subgraph,
not the whole graph.
The second step (bottom-to-top) scans through the leaves and tries to
detect the users of the leaves which can be reordered. If the leaves can
be reorder in the best fashion, they are reordered and their user too.
It allows to remove double shuffles to the same ordering of the operands in
many cases and just reorder the user operations instead. Plus, it moves
the final shuffles closer to the top of the graph and in many cases
allows to remove extra shuffle because the same procedure is repeated
again and we can again merge some reordering masks and reorder user nodes
instead of the operands.
Also, patch improves cost model for gathering of loads, which improves
x264 benchmark in some cases.
Gives about +2% on AVX512 + LTO (more expected for AVX/AVX2) for {625,525}x264,
+3% for 508.namd, improves most of other benchmarks.
The compile and link time are almost the same, though in some cases it
should be better (we're not doing an extra instruction scheduling
anymore) + we may vectorize more code for the large basic blocks again
because of saving scheduling budget.
Differential Revision: https://reviews.llvm.org/D105020
Need to fix several cost-related problems. The final type may be defined
incorrectly because of to early definition (we may end up with the wider
type), the CommonCost should not be redefined in ExtractElements
cost related calculations and the shuffle of the final insertelements
vectors should be calculated as a cost of single vector permutations
+ costs of two vector permutations for other n-1 incoming vectors.
Differential Revision: https://reviews.llvm.org/D106578
Need to fix several cost-related problems. The final type may be defined
incorrectly because of to early definition (we may end up with the wider
type), the CommonCost should not be redefined in ExtractElements
cost related calculations and the shuffle of the final insertelements
vectors should be calculated as a cost of single vector permutations
+ costs of two vector permutations for other n-1 incoming vectors.
Differential Revision: https://reviews.llvm.org/D106578
I have added a new FastMathFlags parameter to getArithmeticReductionCost
to indicate what type of reduction we are performing:
1. Tree-wise. This is the typical fast-math reduction that involves
continually splitting a vector up into halves and adding each
half together until we get a scalar result. This is the default
behaviour for integers, whereas for floating point we only do this
if reassociation is allowed.
2. Ordered. This now allows us to estimate the cost of performing
a strict vector reduction by treating it as a series of scalar
operations in lane order. This is the case when FP reassociation
is not permitted. For scalable vectors this is more difficult
because at compile time we do not know how many lanes there are,
and so we use the worst case maximum vscale value.
I have also fixed getTypeBasedIntrinsicInstrCost to pass in the
FastMathFlags, which meant fixing up some X86 tests where we always
assumed the vector.reduce.fadd/mul intrinsics were 'fast'.
New tests have been added here:
Analysis/CostModel/AArch64/reduce-fadd.ll
Analysis/CostModel/AArch64/sve-intrinsics.ll
Transforms/LoopVectorize/AArch64/strict-fadd-cost.ll
Transforms/LoopVectorize/AArch64/sve-strict-fadd-cost.ll
Differential Revision: https://reviews.llvm.org/D105432
The incoming values for PHI nodes may come from unreachable BasicBlocks,
need to handle this case.
Differential Revision: https://reviews.llvm.org/D106264
Part of D105020. Also, fixed FIXMEs that need to use wider vector type
when trying to calculate the cost of reused scalars. This may cause
regressions unless D100486 is landed to improve the cost estimations
for long vectors shuffling.
Differential Revision: https://reviews.llvm.org/D106060
The cost of the InsertSubvector shuffle kind cost is not complete and
may end up with just extracts + inserts costs in many cases. Added
a workaround to represent it as a generic PermuteSingleSrc, which is
still pessimistic but better than InsertSubvector.
Differential Revision: https://reviews.llvm.org/D105827
This bug was introduced with D105730 / 25ee55c0ba .
If we are not converting all of the operations of a reduction
into a vector op, we need to preserve the existing select form
of the remaining ops. Otherwise, we are potentially leaking
poison where it did not in the original code.
Alive2 agrees that the version that freezes some inputs
and then falls back to scalar is correct:
https://alive2.llvm.org/ce/z/erF4K2
Simon Pilgrim